Optimizing processor operation in a processing system including one or more digital filters

ABSTRACT

A method for optimizing processor operation in a processing system including one or more digital filters is provided according to the invention. The method includes generating initial filter coefficients for the one or more digital filters of the processing system, determining one or more initial filter coefficients for at least one digital filter of the one or more digital filters that can be dropped and dropping the one or more initial filter coefficients. Dropping the one or more initial filter coefficients reduces a total number of filter coefficients to be used by the processing system.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a processing system, and moreparticularly, to optimizing processor operation in a processing systemincluding one or more digital filters.

2. Statement of the Problem

Vibratory flowmeters typically include a processing system that operatesa driver to vibrate a flowtube assembly, receives pick-off sensorsignals in response, processes the pick-off sensor response signals, andcommunicates with external devices. The processing system processes thepick-off sensor response signals in order to generate one or moremeasurements, such as one or more flow characteristics. The one or moreflow characteristics can include a vibration frequency, a phasedifference or time difference between leading and lagging portions of aflow tube or tubes, mass flow rate, density, viscosity, pressure, andothers.

The processing system can receive and digitize analog inputs. Thedigitizing may require sampling of the analog signal(s). The processingsystem runs at a fixed clock rate and samples the pick-off sensorresponse signals at a fixed sampling rate. According to the NyquistTheorem, the sampling rate must be at least twice the frequency beingsampled.

One processing system application is a flowmeter, such as a vibratoryflowmeter, where the processing system receives analog vibrationalsignals and determines frequency and phase characteristics of thevibrational signals, among other things In the past, the sampling ratehas been set at a high enough frequency to accommodate various models offlowmeters, including low frequency flow meters and high frequency flowmeters. This can be done for economic reasons, such as to avoid themanufacturing and tracking of multiple models of flowmeter electronics.Typically, the sampling rate has been set at 2,000 Hertz (i.e., 2 kHz),where most vibratory flowmeters operate at frequencies well below 1 kHz.

In the prior art, processing system speed is generally not a concern.The prior art processing system is typically chosen for durability andcapacity. If the processing system has a high enough clock speed, theprocessing system will be able to adequately process the 2 kHz samplesin order to generate the one or more flow characteristics (and may beable to perform additional processing and communications and controlfunctions). Clock speed and sampling rate of the flowmeter electronicsare generally configured for wide applicability and therefore have beenchosen to significantly exceed flowmeter vibration rates. Processingsystem power consumption has not been a concern in the prior art andtherefore it has been acceptable practice to set a generous samplingrate.

The drawback in using a high sampling rate is that it requires a highprocessing system clock rate. The high clock rate in turn forces ahigher power consumption.

In some applications, it is desired to keep power consumption as low aspossible. Consequently, high power consumption by the processing systemis problematic.

Aspects of the Invention

In one aspect of the invention, a method for optimizing processoroperation in a processing system including one or more digital filterscomprises:

generating initial filter coefficients for the one or more digitalfilters;

determining one or more initial filter coefficients for at least onedigital filter of the one or more digital filters that can be dropped;and

dropping the one or more initial filter coefficients, wherein droppingthe one or more initial filter coefficients reduces a total number offilter coefficients to be used by the processing system.

Preferably, the method further comprises a subsequent step ofprogramming the filter coefficients into the processing system.

Preferably, the dropping further comprises dropping the one or moreinitial filter coefficients from one or more predetermined digitalfilters.

Preferably, a digital filter of the one or more digital filters includesnon-symmetric filter coefficients.

Preferably, a digital filter of the one or more digital filters includessymmetric filter coefficients.

Preferably, a digital filter of the one or more digital filters includessymmetric filter coefficients and wherein symmetric filter coefficientsare dropped singly or in pairs.

Preferably, the method further comprises comparing one or moreprocessing system measurements to a predetermined power usage thresholdduring operation, if the one or more processing system measurementsexceeds the predetermined power usage threshold, then determining one ormore operational filter coefficients for at least one digital filter ofthe one or more digital filters that can be dropped, and dropping theone or more operational filter coefficients, wherein dropping the one ormore operational filter coefficients reduces a total number ofoperational filter coefficients to be used by the processing systemduring at least a current main loop processing iteration.

In one aspect of the invention, a method for adaptively optimizingprocessor operation in a processing system including one or more digitalfilters comprises:

comparing one or more processing system measurements to a predeterminedpower usage threshold during operation;

if the one or more processing system measurements exceeds thepredetermined power usage threshold, then determining one or more filtercoefficients for at least one digital filter of the one or more digitalfilters that can be dropped; and

dropping the one or more filter coefficients, wherein dropping the oneor more filter coefficients reduces a total number of filtercoefficients to be used by the processing system.

Preferably, the dropping further comprises dropping one or more filtercoefficients from one or more predetermined digital filters.

Preferably, the method further comprises iteratively performing thecomparing, determining, and processing steps.

Preferably, a digital filter of the one or more digital filters includesnon-symmetric filter coefficients.

Preferably, a digital filter of the one or more digital filters includessymmetric filter coefficients.

Preferably, a digital filter of the one or more digital filters includessymmetric filter coefficients and wherein symmetric filter coefficientsare dropped singly or in pairs.

Preferably, the method further comprises determining a number ofoperational filter coefficients to be dropped based on an amount bywhich the one or more processing system measurements exceeds thepredetermined power usage threshold.

Preferably, the method further comprises the preliminary steps ofgenerating initial filter coefficients for the one or more digitalfilters, determining one or more initial filter coefficients for atleast one digital filter of the one or more digital filters that can bedropped, and dropping the one or more initial filter coefficients,wherein dropping the one or more initial filter coefficients reduces thetotal number of filter coefficients to be used by the processing system.

In one aspect of the invention, a method for optimizing processoroperation in a processing system including one or more digital filterscomprises:

generating filter coefficients for the one or more digital filters;

determining one or more initial filter coefficients and one or moreoperational filter coefficients for at least one digital filter of theone or more digital filters that can be dropped;

dropping the one or more initial filter coefficients, wherein droppingthe one or more initial filter coefficients reduces a total number offilter coefficients to be used by the processing system;

programming the filter coefficients into the processing system;

comparing one or more processing system measurements to a predeterminedpower usage threshold during operation; and

if the one or more processing system measurements exceeds thepredetermined power usage threshold, then dropping the one or moreoperational filter coefficients, wherein dropping the one or more filtercoefficients further reduces a total number of filter coefficients to beused by the processing system.

Preferably, the dropping further comprising dropping the one or moreinitial filter coefficients from one or more predetermined digitalfilters.

Preferably, a digital filter of the one or more digital filters includesnon-symmetric filter coefficients.

Preferably, a digital filter of the one or more digital filters includessymmetric filter coefficients.

Preferably, a digital filter of the one or more digital filters includessymmetric filter coefficients and wherein symmetric filter coefficientsare dropped singly or in pairs.

Preferably, the method further comprises iteratively performing thecomparing and dropping steps for the one or more operational filtercoefficients.

Preferably, the method further comprises determining a number ofoperational filter coefficients to be dropped based on an amount bywhich the one or more processing system measurements exceeds thepredetermined power usage threshold.

DESCRIPTION OF THE DRAWINGS

The same reference number represents the same element on all drawings.It should be understood that the drawings are not necessarily to scale.

FIG. 1 shows a processing system according to an embodiment of theinvention.

FIG. 2 is a flowchart of a method for optimizing processor operation ina processing system including one or more digital filters according toan embodiment of the invention.

FIG. 3 shows a filter response for a standard Hilbert digital filterformed with one hundred fifty filter coefficients.

FIG. 4 shows the filter of FIG. 3 where some of the filter coefficientshave been dropped according to an embodiment of the invention.

FIG. 5 shows the processing system after filter coefficients have beendropped according to an embodiment of the invention.

FIG. 6 is a flowchart of a method for adaptively optimizing processoroperation in a processing system including one or more digital filtersaccording to an embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

FIGS. 1-6 and the following description depict specific examples toteach those skilled in the art how to make and use the best mode of theinvention. For the purpose of teaching inventive principles, someconventional aspects have been simplified or omitted. Those skilled inthe art will appreciate variations from these examples that fall withinthe scope of the invention. Those skilled in the art will appreciatethat the features described below can be combined in various ways toform multiple variations of the invention. As a result, the invention isnot limited to the specific examples described below, but only by theclaims and their equivalents.

FIG. 1 shows a processing system 103 according to an embodiment of theinvention. The processing system 103 can include an interface 101. Theprocessing system 103 receives sensor signals from a sensor of somemanner. For example, in one embodiment the sensor comprises a vibratoryflowmeter assembly including pick-off/velocity sensor signals that sensea vibrational response of a flowmeter assembly and generatecorresponding analog vibrational response signals. The processing system103 processes the sensor signals in order to obtain one or moreprocessing system measurements, such as flow characteristics 112 of aflow material flowing through a flowmeter assembly, for example.Consequently, the processing system 103 can determine one or more of aphase difference, a frequency, a time difference (Δt), a density, a massflow rate, a viscosity, and a volume flow rate from the sensor signalsof a flowmeter assembly, for example.

The processing system 103 can comprise a general purpose computer, amicroprocessing system, a logic circuit, or some other general purposeor customized processing device. The processing system 103 can bedistributed among multiple processing devices. The processing system 103can include any manner of integral or independent electronic storagemedium, such as the storage system 104.

The storage system 104 can store parameters and data, software routines,constant values, and variable values. In addition, the storage system104 can store one or more digital filters that are employed by theprocessing routine 110, wherein a digital filter includes a series ofcoefficients.

In the embodiment shown, the storage system 104 stores a first digitalfilter A 120, a second digital filter B 121, a third digital filter C122, and a fourth digital filter D 123. The filter sets shown are givenmerely for illustration. It should be understood that the processingsystem 103 can include any needed number and type of digital filters.

The digital filters can comprise any manner of digital filters,including finite impulse response (FIR) and infinite impulse response(IIR) filters. The digital filters can comprise low pass, bandpass, orhigh pass filters. The digital filters can perform filtering,phase-shifting, and windowing functions, among other things Other filtertypes and filter uses are contemplated and are within the scope of thedescription and claims.

A digital filter can be used to eliminate frequencies outside of afrequency band of interest, such as through the use of any variety oflow pass, bandpass, or high pass filter.

A digital filter can be used for decimation, wherein some samples areeliminated in order to reduce the sampling rate. Decimation can be usedto vary the number of frequency bands to be processed, for example.

A digital filter can be used for phase-shifting a digital signalwaveform, such as through use of a Hilbert transform or Hilbert filter.The Hilbert transform or filter can phase-shift the input waveform byninety degrees, for example. The phase-shifting can be used indetermining the one or more flow characteristics.

A digital filter can be used for windowing, wherein frequencies outsideof a window are eliminated. Windowing can be performed after aprocessing stage, such as to cut off tails generated by Fourierprocessing.

In some embodiments, a measurement can be derived from a phase-shiftingof one or more received signals. This advantageously reduces therequired processing time.

A digital filter includes a set or chain of coefficients that correspondto and are applied against the digitally sampled waveform of interest.The filter is designed based on the desired output to be obtained fromthe input waveform. When the digital input waveform is filtered usingthe coefficients of the digital filter, the filtering process passes atleast a portion of the frequencies or frequency bands of interest, whilerejecting non-desired frequencies or frequency bands.

The series of filter coefficients can be symmetric. For example, thefirst and last coefficients (A₁ and A₁₀₀) of the first digital filter A120 can be the same, the second and second-to-last coefficients (A₂ andA₉₉) can be the same, and so on.

The series of coefficients can be non-symmetric. Each coefficient can beunique, such as shown in the second digital filter B 121.

The number of filter coefficients may depend on various factors. Forexample, the number of filter coefficients can be chosen according tothe frequency span of the input waveform, the frequency span of thefiltered result (i.e., the width of the filter transfer function), thedesired shape of the filter transfer function, the sharpness or roll-offof the transfer function, etc.

Filter performance can generally be improved and/or the transformfunction can be formed in a more complex shape if a greater number offilter coefficients are employed. However, the increased number ofmultiplications (or other filtering operations) necessitated by thelarge number of coefficients will increase the required processing time.Consequently, the desired resolution and accuracy entails a trade-offbetween frequency discrimination versus processing time.

In addition, the processing system 103 can implement multiple digitalfilters. Processing the input waveform through multiple digital filtersin a single iteration can consume considerable processing time.

A high sampling rate leads to a large number of filtering operations. Alarge number of filtering operations subsequently cause an undesirablylong loop time and consequently a slower response by the processingsystem 103. However, the sampling frequency can be limited if theinstrument coupled to the processing system 103, such as a flowmeterproviding a vibrational frequency, is low enough that the samplingfrequency can be reduced and yet still meet the Nyquist criteria.

A large loop time may prevent the processing of all incoming samples.Further, a large loop time will result in a high level of powerconsumption by the processing system 103. If the processing system 103takes too much processing time per main loop iteration, othercomputations and/or processing routines can be affected. The end resultcan be an inaccurate and unreliable result and even reset or shut-downof the processing system 103.

FIG. 2 is a flowchart 200 of a method for optimizing processor operationin a processing system including one or more digital filters accordingto an embodiment of the invention. The method can be employed tooptimize response time. The method can be employed to optimize powerconsumption. In step 201, one or more digital filters are generated foruse with the processing system, including initial filter coefficients.

In step 202, one or more initial filter coefficients of at least onedigital filter are determined to be droppable. The one or more initialfilter coefficients are determined to be able to be dropped withoutunacceptably affecting the filtering operation. Dropping filtercoefficients will result in an increase in noise in the filter output.Dropping filter coefficients will result in a decrease in processorbandwidth. As a consequence, coefficient dropping is a trade-off betweenprocessing speed and power consumption versus noise and processorbandwidth.

The one or more initial filter coefficients can comprise coefficients ofany of the digital filters of the processing system. The one or moreinitial filter coefficients can be targeted from predetermined filters.

In step 203, the identified one or more initial filter coefficients aredropped from respective filters. Dropping the one or more initial filtercoefficients reduces a total number of filter coefficients to be used bythe processing system. The one or more initial filter coefficients canbe therefore removed from one or more digital filters. In someembodiments, dropped coefficients are dropped from either (or both) endsof a string of coefficients making up the digital filter. However, thedropped filter coefficients can occur anywhere in a string of filtercoefficients. The remaining initial filter coefficients are programmedinto the processing system.

FIG. 3 shows a filter response for a standard Hilbert digital filterformed with one hundred fifty filter coefficients. In this figure, thefilter response is shaped and determined by the full one hundred fiftyfilter coefficients. Increasing the number of coefficients can increasethe roll-off rate of signals toward either end of the filter envelopeand can change the shape of the frequency response. As a consequence,increasing the number of filter coefficients can improve the filteringresult at the expense of increased processing time.

FIG. 4 shows the filter of FIG. 3 where some of the filter coefficientshave been dropped according to an embodiment of the invention. In thisexample, thirty coefficients have been dropped. It can be seen that theeffect is confined to the left and right edges of the filter transferfunction and the center region of the filter transfer function isrelatively flat and unchanged. Changes to the center region may havesome effects on the end result of the filtering operation. In contrast,dropping coefficients at the ends of the filter mainly affects thefilter response at the periphery and therefore has minimal effect on thedesired signal.

The one or more filter coefficients can include two or more coefficientsdropped from a single digital filter. For example, where a digitalfilter comprises symmetric or partially symmetric coefficients, a pairof coefficients can be dropped. Further, even where a digital filterdoes not have symmetric coefficients, multiple filter coefficients canbe dropped, such as a number of adjacent coefficients at an end of afilter.

The downside to dropping filter coefficients may be a drop inrepeatability in the filtered result due to increased noise. This is nota given, however, and if a minimal number are dropped there may not beany effect on the filtering of the vibrational waveform.

Referring again to FIG. 2, in step 204 the one or more digital filtersare programmed into an appropriate electronics, such as the digitalfilters 120-123 in the processing system 103 shown in FIG. 1. Forexample, the one or more digital filters are programmed into the storagesystem 104. The one or more digital filters 120-123 can now be used bythe processing routine 110. It should be understood that the digitalfilters can be stored in any manner, including in onboard processingsystem memory, as shown. Alternatively, the digital filters can bestored in any manner of external storage coupled to the processingsystem 103.

FIG. 5 shows the processing system 103 after filter coefficients havebeen dropped according to an embodiment of the invention. The figureshows several examples of filter coefficient dropping when compared tothe processing system 103 of FIG. 1.

The first digital filter A 120 has not been changed. The second digitalfilter B 121 has had a last filter coefficient, coefficient B₅₀, droppedfrom the filter. The third digital filter C 122 has first and lastfilter coefficients C₁ and C₁₀₀ dropped from the filter. The fourthdigital filter D 123 has the two first coefficients D₁ and D₂ and thelast two coefficients D₉₉ and D₁₀₀ dropped from the filter. Each of theaffected filters will as a consequence require fewer filteringoperations.

FIG. 6 is a flowchart 600 of a method for adaptively optimizingprocessor operation in a processing system including one or more digitalfilters according to the invention. As previously discussed, filtercoefficients can be dropped in order to speed up a response time of theprocessing system and/or in order to reduce power consumption. In step601, the one or more digital filters are generated for use in theprocessing system, as previously discussed.

In step 602, one or more filter coefficients of at least one digitalfilter are determined to be droppable, as previously discussed. Thefilter coefficients to be dropped can comprise initial filtercoefficients, operational filter coefficients, or both initial andoperational filter coefficients. The initial filter coefficients are tobe dropped before programming the processing system and the operationalfilter coefficients are to be temporarily or permanently dropped duringoperation of the processing system.

In step 603, the one or more digital filters are programmed into theprocessing system. The droppable operational filter coefficients can bestill included in the digital filters and can comprise a designation offilter coefficients to be adaptively dropped during operation or at somepoint in the future.

Alternatively, a first (initial) portion of the designated droppablefilter coefficients can be dropped before programming the electronicsand a second (operational) portion can be adaptively dropped duringoperation. Consequently, this flowchart could be modified to includestep 203 of FIG. 2 before step 603 of this figure.

In step 604, processing system operation is commenced.

In step 605, operational conditions are monitored by the processingsystem. If there is an operational change, such as a change in the oneor more processing system measurements, then the method proceeds to step606. Otherwise, if operation is within normal bounds (see below), thenthe method loops back to step 605 and monitors for a change inoperational conditions.

The monitoring can include comparing the one or more processing systemmeasurements to a predetermined operational threshold, wherein thepredetermined operational threshold reflects or relates to anundesirable electrical power usage level. The predetermined operationalthreshold can comprised a fixed or dynamic threshold and can be linkedto or controlled by internal variables in the processing system.

In some vibratory flowmeter embodiments, the predetermined operationalthreshold can comprise a time difference (Δt) threshold. The timedifference (Δt) comprises a time difference in signals from the pick-offsensors and therefore between leading and lagging portions of a flowconduit of the vibratory flowmeter. Consequently, if the time difference(Δt) becomes too large, then the vibrational amplitude being generatedby the vibratory flowmeter has become excessive and will likely requirea high level of power consumption. The power consumption canconsequently be reduced somewhat by dropping some of the filtercoefficients, temporarily or for an indefinite time period. In someembodiments, the predetermined operational threshold can comprise astandard deviation of the time difference (Δt) from a predeterminedvalue.

In some vibratory flowmeter embodiments, the predetermined operationalthreshold can comprise a frequency (f) threshold. The frequency (f)comprises a frequency response received from a pick-off sensor(s).Consequently, if the frequency (f) falls outside of a normal or expectedrange, then the operation of the vibratory flowmeter has become abnormaland will likely require a high level of power consumption. In someembodiments, the predetermined operational threshold can comprise astandard deviation of the frequency (f) from a predetermined value.

In some vibratory flowmeter embodiments, the predetermined operationalthreshold can comprise a phase difference (Δθ) threshold. The phasedifference (Δθ) comprises a phase difference in the vibrational responsesignals received from the pick-off sensors of the vibratory flowmeter.Consequently, if the phase difference (Δθ) falls outside of a normal orexpected range, then the operation of the vibratory flowmeter has becomeabnormal and will likely require a high level of power consumption. Insome embodiments, the predetermined operational threshold can comprise astandard deviation of the phase difference (Δθ) from a predeterminedvalue.

In step 606, because the processing system has determined that the oneor more processing system measurements have deviated beyond a normaloperational range, then the previously denoted droppable operationalfilter coefficients are dropped. The dropping can occur for any desiredtime period, including indefinitely. For example, the dropping can occurfor one or more main loop iterations of the processing system. However,other time periods are contemplated and are within the scope of thedescription and claims.

In step 607, the method can further determine if additional operationalfilter coefficients should be dropped (where some operational filtercoefficients have already been dropped). The method determines thenumber of operational filter coefficients to be dropped based on anamount by which the one or more processing system measurements exceedsthe predetermined power usage threshold. This step can assess theseverity of the power consumption and can determine a graded level ofoperational coefficient dropping. For example, if previously droppedoperational filter coefficients have had not enough effect, then themethod can drop additional operational filter coefficients as needed. Ifmore are to be dropped, then the method can loop back to step 606 anddrop additional operational coefficients. In this manner, theoperational filter coefficients can be dropped in an escalating fashionin order to avoid unnecessary impact on filtering operations. If no moreoperational filter coefficients are to be dropped, then the methodbranches back to step 605 and continues to monitor for operationalchanges.

In some embodiments, a user can participate in choosing initial and/oroperational filter coefficients to be dropped. Dropping filtercoefficients will enable a user to significantly increase a responsespeed of a processing system and the associated instrument or meter. Forexample, a user can specify the droppable operational filtercoefficients. The associated instrument can operate normally undercertain conditions. Under adverse or abnormal conditions, which can bespecified by the user, the processing system can drop a predeterminednumber of filter coefficients and increase a response speed, at theexpense of more noise. This gives the user increased control and greateroperational flexibility. This allows the user to determine the optimalresponse time and/or power versus an acceptable noise and/or processorbandwidth for a particular application. This can be achieved withoutswitching between multiple filters within the processing system orinstrument.

1. A method for optimizing processor operation in a processing systemincluding one or more digital filters, the method comprising: generatinginitial filter coefficients for the one or more digital filters;determining one or more initial filter coefficients for at least onedigital filter of the one or more digital filters that can be dropped;and dropping the one or more initial filter coefficients, whereindropping the one or more initial filter coefficients reduces a totalnumber of filter coefficients to be used by the processing system. 2.The method of claim 1, further comprising a subsequent step ofprogramming the filter coefficients into the processing system.
 3. Themethod of claim 1, with the dropping further comprising dropping the oneor more initial filter coefficients from one or more predetermineddigital filters.
 4. The method of claim 1, wherein a digital filter ofthe one or more digital filters includes non-symmetric filtercoefficients.
 5. The method of claim 1, wherein a digital filter of theone or more digital filters includes symmetric filter coefficients. 6.The method of claim 1, wherein a digital filter of the one or moredigital filters includes symmetric filter coefficients and whereinsymmetric filter coefficients are dropped singly or in pairs.
 7. Themethod of claim 1, further comprising: comparing one or more processingsystem measurements to a predetermined power usage threshold duringoperation; if the one or more processing system measurements exceeds thepredetermined power usage threshold, then determining one or moreoperational filter coefficients for at least one digital filter of theone or more digital filters that can be dropped; and dropping the one ormore operational filter coefficients, wherein dropping the one or moreoperational filter coefficients reduces a total number of operationalfilter coefficients to be used by the processing system during at leasta current main loop processing iteration.
 8. A method for adaptivelyoptimizing processor operation in a processing system including one ormore digital filters, the method comprising: comparing one or moreprocessing system measurements to a predetermined power usage thresholdduring operation; if the one or more processing system measurementsexceeds the predetermined power usage threshold, then determining one ormore filter coefficients for at least one digital filter of the one ormore digital filters that can be dropped; and dropping the one or morefilter coefficients, wherein dropping the one or more filtercoefficients reduces a total number of filter coefficients to be used bythe processing system.
 9. The method of claim 8, with the droppingfurther comprising dropping one or more filter coefficients from one ormore predetermined digital filters.
 10. The method of claim 8,iteratively performing the comparing, determining, and processing steps.11. The method of claim 8, wherein a digital filter of the one or moredigital filters includes non-symmetric filter coefficients.
 12. Themethod of claim 8, wherein a digital filter of the one or more digitalfilters includes symmetric filter coefficients.
 13. The method of claim8, wherein a digital filter of the one or more digital filters includessymmetric filter coefficients and wherein symmetric filter coefficientsare dropped singly or in pairs.
 14. The method of claim 8, furthercomprising determining a number of operational filter coefficients to bedropped based on an amount by which the one or more processing systemmeasurements exceeds the predetermined power usage threshold.
 15. Themethod of claim 8, further comprising the preliminary steps of:generating initial filter coefficients for the one or more digitalfilters; determining one or more initial filter coefficients for atleast one digital filter of the one or more digital filters that can bedropped; and dropping the one or more initial filter coefficients,wherein dropping the one or more initial filter coefficients reduces thetotal number of filter coefficients to be used by the processing system.16. A method for optimizing processor operation in a processing systemincluding one or more digital filters, the method comprising: generatingfilter coefficients for the one or more digital filters; determining oneor more initial filter coefficients and one or more operational filtercoefficients for one or more digital filters of the one or more digitalfilters that can be dropped; dropping the one or more initial filtercoefficients, wherein dropping the one or more initial filtercoefficients reduces a total number of filter coefficients to be used bythe processing system; programming the filter coefficients into theprocessing system; comparing one or more processing system measurementsto a predetermined power usage threshold during operation; and if theone or more processing system measurements exceeds the predeterminedpower usage threshold, then dropping the one or more operational filtercoefficients, wherein dropping the one or more filter coefficientsfurther reduces a total number of filter coefficients to be used by theprocessing system.
 17. The method of claim 16, with the dropping furthercomprising dropping the one or more initial filter coefficients from oneor more predetermined digital filters.
 18. The method of claim 16,wherein a digital filter of the one or more digital filters includesnon-symmetric filter coefficients.
 19. The method of claim 16, wherein adigital filter of the one or more digital filters includes symmetricfilter coefficients.
 20. The method of claim 16, wherein a digitalfilter of the one or more digital filters includes symmetric filtercoefficients and wherein symmetric filter coefficients are droppedsingly or in pairs.
 21. The method of claim 16, iteratively performingthe comparing and dropping steps for the one or more operational filtercoefficients.
 22. The method of claim 16, further comprising determininga number of operational filter coefficients to be dropped based on anamount by which the one or more processing system measurements exceedsthe predetermined power usage threshold.